Disease detection in banana trees using an image processing-based thermal camera

Author:

Anasta N,Setyawan F X A,Fitriawan H

Abstract

Abstract Banana is a fruit plant that is widely produced in Indonesia. Unfortunately, this plant is very susceptible to diseases, which can reduce the crop’s quality and quantity. This paper proposes disease detection in banana plants using a thermal camera. The detection is carried out using image processing techniques with multilevel thresholding methods. The image is captured using a thermal camera; then, the image is preprocessed to suit what is desired. After that, the image produced by the thermal camera is carried out by an image registration process so that the position is the same as the image taken using a digital camera. The image processing result is compared with the ground truth image obtained from a digital camera to determine the effectiveness of the proposed method. The proposed method’s effectiveness is measured using the parameters Recall, Precision, F-measure, and Accuracy. The effectiveness of the proposed method is quite effective because it produces parameter values above 80%, namely the recall value of 85.4%, the Precision of 89.35%, the F measure of 87.33%, and the accuracy of 92.8%.

Publisher

IOP Publishing

Subject

General Engineering

Reference21 articles.

1. Pengaruh Varietas dan Umur Tanaman Berbeda terhadap Jumlah Populasi dan Tingkat Serangan Hama dan Penyakit Pisang (Musa sp.) di Kabupaten Sukabumi;Triwidodo;Jurnal Agrikultura,2020

2. Detection and Identification of Banana-associated Phytoplasma Using Nested-PCR Method;Sibarani;Jurnal Perlindungan Tanaman Indonesia,2019

3. Detection of plant leaf diseases using image segmentation and soft computing techniques;Singh;Information Processing in Agriculture,2017

4. Plant Disease Prediction Using Image Processing Techniques - A Review;Varshney;International Journal of Computer Science and Mobile Computing,2016

5. Banana Leaf Disease Identification Technique;Vipinadas;International Journal of Advanced Engineering Research and Science,2016

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